Fuzzy Greedy Search: A Deterministic Heuristic for Combinatorial Optimization

Kaveh Sheibani
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Kaveh Sheibani: ORLab Analytics, Vancouver, Canada

International Journal of Applied Management Sciences and Engineering (IJAMSE), 2017, vol. 4, issue 2, 1-12

Abstract: This paper presents mathematics of the so-called fuzzy greedy evaluation concept which can be integrated into approaches for hard combinatorial optimization problems. The proposed method evaluates objects in a way that combines fuzzy reasoning with a greedy mechanism, thereby exploiting a fuzzy solution space using greedy methods. Given that the greedy algorithms are computationally inexpensive compared to other more sophisticated methods for combinatorial optimization; this shows practical significance of using the proposed approach. The effectiveness and efficiency of the proposed method are demonstrated on permutation flow-shop scheduling as one of the most widely studied hard combinatorial optimization problems in the area of operational research and management science.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jamse0:v:4:y:2017:i:2:p:1-12

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